A systematic strategy using a reconstructed genome-scale metabolic network for pathogen Streptococcus pneumoniae D39 to find novel potential drug targets

Author:

Pedram Narges1,Rashedi Hamid1,Motamedian Ehsan2ORCID

Affiliation:

1. Department of Biotechnology, School of Chemical Engineering, College of Engineering, University of Tehran, P.O. Box 11155–4563, Tehran, Iran

2. Department of Biotechnology, Faculty of Chemical Engineering, Tarbiat Modares University, P.O. Box 14155–4838, Tehran, Iran

Abstract

ABSTRACT Streptococcus pneumoniae is a Gram-positive bacterium that is one of the major causes of various infections such as pneumonia, meningitis, otitis media and endocarditis. Since antibiotic resistance of S. pneumoniae is pointed out as a challenge in the treatment of these infections, more studies are required to focus on disease prevention. In this research, a first manually curated genome-scale metabolic network of the pathogen S. pneumoniae D39 was reconstructed based on its genome annotation data, and biochemical knowledge from literature and databases. The model was validated by amino acid auxotrophies, gene essentiality analysis, and different carbohydrate sources. Then, a two-stage strategy was developed to find target genes for growth reduction of the pathogen and their importance in the various infection sites. In the first stage, growth-associated genes were identified by integration of transcriptomic data with the model and in the second stage, the importance of each gene in the metabolism for growth was evaluated using principal component analysis. The reports presented in the literature confirm the effect of some found genes on the growth of S. pneumoniae.

Funder

Iran National Science Foundation

Publisher

Oxford University Press (OUP)

Subject

Infectious Diseases,Microbiology (medical),General Immunology and Microbiology,General Medicine,Immunology and Allergy

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. A review of advances in integrating gene regulatory networks and metabolic networks for designing strain optimization;Journal of King Saud University - Computer and Information Sciences;2024-07

2. Unveiling the potential of systems biology in biotechnology and biomedical research;Systems Microbiology and Biomanufacturing;2024-06-24

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